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The Challenge

Image with "A call to visualize: USDOT is hosting this challenge to generate new perspectives and empower a broad group of innovators to push the boundaries of transportation collaboration." as text

Currently transportation decision makers have a limited number of analytical visualization tools available that reveal insights, and even fewer focused on safety and prevention of serious crashes.  A new opportunity lies in the rapid growth and advancement in technology and analytics markets combined with the volume and variety of transportation and other data now collected by the public and private sectors. 

This is why the Solving for Safety Visualization Challenge is looking for the best innovators from the business and research communities, including technology companies, analytics firms, transportation carriers, industry associations, research institutions, universities, mapping and visualization providers to tackle this challenge.  Analytical visualization tools can cast new light on the data to reveal insights not seen though tabular analysis. The Challenge has been created to advance the use of safety data visualizations for answering analytical questions related to surface transportation system safety.

In this challenge, Solvers will compete for cash prizes by developing innovative analytical visualization tools to gain insights into fatalities and serious injuries on the U.S. road and rail systems that policymakers, providers, and operators can use to inform the development of safety solutions. 

Analytical Visualization Tools

Challenge Solvers will choose between two types of analytical visualization tools to develop:

  • Discover Insights Tools will analyze data to reveal patterns and trends, and will use compelling visualizations to explain what is happening, understand the meaning behind the data, and draw conclusions. These tools often combine disparate data sets and allow a user to ask a question and search for answers visually.
  • Simulation Tools will assist in decision-making by visualizing data, mathematical, and statistical models to identify issues, determine correlations, and assign probabilities with a degree of accuracy.  Developed using existing models and data, including those provided by USDOT and Innovation Agents, this type of tool will allow users to visualize the outputs of model simulations and scenarios, highlighting the different conditions and the results of sensitivity and parametric analysis to visually assist in decision-making.

The USDOT is looking for solutions that bring novel concepts and perspectives to existing models and data to develop analytical visualization tools that provide life-saving insights for transportation safety.  Solvers should use innovation and creativity to further define the tools.   Tools can range from dashboards using disparate data sets, to spatial analysis via maps, to virtual or augmented reality scenarios, to image and image analysis, to social media mining and beyond. The tools can be powered by models and data provided by USDOT, Challenge Innovation Agents and/or resources Solvers have access to through their organizations or partners. See the Challenge Resources page for a sample list of datasets and tools.

Safety Focus Areas

Challenge Solvers will develop analytical visualization tools to complement existing USDOT projects while addressing one or more of the following safety focus areas:

  1. Vulnerable System Users – these include non-motorized road users, such as pedestrians and cyclists, as well as motorcyclists and persons with disabilities or reduced mobility and orientation, such as those with declining vision and hearing.  Ongoing work at USDOT has identified those who are more at risk on the road system, but beyond the police reports and behavior research, we’re missing pieces of the story that will improve how we protect these users. Questions Solvers might address:
  • Between 2013 and 2016 there was a 25-percent increase in pedestrians killed in traffic crashes (  A disproportionate share of these pedestrian fatalities involved males, occurred in urban locations, and took place after dark. How can data visualization tools support decision-makers in learning from the relationships among various contributory crash risk factors that are specific to their communities?
  • A Crash Modification Factor (CMF) is a multiplicative factor that indicates the proportion of crashes that would be expected after implementing a countermeasure. Examples of countermeasures include installing a traffic signal, increasing the width of road edge lines, and installing a median barrier.  We know the CMFs and proven safety countermeasures work, but how could we help decision makers make those choices?
  1. Conflict Points Impacts – these are locations where user paths intersect, including road intersections and rail grade crossings. Conflict points are categorized as crossing, merging (or joining) and diverging (or separating). We’re investigating the leading conflict points of motor vehicle crashes, but we don’t fully understand the difference between near-misses and impacts at these points. Questions Solvers might address:
  • Much of the nation is built around the railroad system. By developing around this infrastructure, we have unintentionally created conflict points that users are drawn to, often putting disadvantaged communities at greatest risk. How can data visualization tools support urban planners to identify which grade crossing are more prone to accidents and what strategies to employ to reduce the risk?
  • In the United States, over the last several years an average of one-quarter of traffic fatalities and roughly half of all traffic injuries are attributed to intersections (  Strategies to address roadway intersection safety are diverse. Strategies are often engineering based, including geometric design and application of traffic control devices (such as signs, markings and signals) and have a foundation in human factors. Quite often, it is a combination of these strategies that is needed to truly solve a problem. How can we visually compare the safety impacts of traditional signals, roundabouts, protected left turns?
  1. High Risk Factors – these include young drivers, impaired drivers, drowsy drivers, older drivers, and speeding drivers.  We’ve identified high risk factors, but we don’t have complete insights on the role of spatial and temporal exposures. Questions Solvers might address:
  • There is a misalignment between human behavior and judgment, and roadway and vehicle design. New, young drivers have a higher crash risk than any other age group. How can data visualization tools support and educate people to improve their driving behaviors? 
  • In 2015, alcohol-impaired-driving fatalities accounted for 29 percent of the total motor vehicle traffic fatalities. How can data visualization tools support first responders’ on-site interventions?


Challenge Solvers will also focus their analytical visualization tools by designing them for use by one or more of the following audiences:

  1. Policy makers and influencers – these are people in Federal, State, and local government agencies, associations, industry bodies.  They attempt to reduce transportation-related fatalities and serious injuries by analyzing safety data to identify safety risks and recommending a series of strategies, incentives or disincentives using personnel, funding, or laws and regulations to address these.
  2. Providers/Operators – these are people in business and government who build and operate the transportation system.  These include vehicle and equipment manufacturers, trucking and rail companies, state and local departments of transportation, law enforcement, and emergency services. They attempt to influence the reduction of transportation related fatalities and serious injuries by analyzing safety data and designing equipment and facilities, performing system diagnostics, evaluating safety effectiveness, and developing operations, countermeasures and techniques to reduce fatalities and serious injuries for users of the transportation system.
  3. Public – these are people who use the transportation system or live in the United States.  These include motor vehicle drivers, motor vehicle passengers, bicyclists and pedestrians.  They have an interest in protecting themselves and others in the community who use the transportation system.

Multiple Tools, Multiple Focus Areas, Multiple Audiences - One Challenge

All ideas will compete against the full pool of entries regardless of the type of tool, safety focus area or audience being proposed.

The Challenge invites creative minds from across the Nation to reveal these missing links.  The business and research communities have the unique set of skills and creativity to step up and revolutionize transportation safety. The transportation safety community has welcomed innovation, but will benefit further from the perspective and skills of other subject areas. To foster new, novel, and innovative analytical visualization tools, USDOT is looking for Solvers and data from a variety of sectors. The USDOT encourages the participation of Solvers from outside the traditional transportation safety arena who will bring innovative methods, procedures, techniques, and strategies when developing solutions.  The USDOT also has an interest in stimulating the integration of new or private sector data sources into the Solvers’ analytical visualization tools.

The USDOT Solving for Safety Visualization Challenge can act as an engine in driving serious crash reduction. By incentivizing innovation, USDOT will attract the best Solvers from around the nation to come up with new tools for visualizing the risks of serious crashes. As with other government competitions, the USDOT Solving for Safety Visualization Challenge aims to create a vibrant community of thinkers and doers who drive revolutionary innovation.

Technology has already changed how most of us get around. Let’s leverage it to change how we view transportation safety.

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The Solving for Safety Visualization Challenge is part of USDOT's Safety Data Initiative


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